Adam argues that the age old business strategy focused on efficiency at scale can become your biggest enemy, the moment the future becomes unpredictable (as it more and more does nowadays). Since efficiency, by design, lock in roles, processes and practices and therefore makes it much harder to change.

An alternative paradigm, more suited to an unpredictable future, is one of responsiveness – being nimble and agile in responding to the changing reality. The challenge of switching from efficiency to responsiveness is a cultural one. Switching from a model based on secrecy, planning and control, to one based on transparency, experimentation and empowerment. The problem gets conflated because those cultural attributes are interrelated: they can be described as “sliders” on these three spectrum, bound together by a rubber band. In order to move one of them in a certain direction, you have to move the others.

He then goes on to illustrate the tension with a few real world examples. And outlines the path for transformation.

But instead of going down tat path, let’s zoom-in on one of these tensions, with the help of Alfred Wagner and another short post:

Alfred takes us 80 years into the past, to Ronald Coase‘s “The Nature of The Firm” and the two fundamental problems that it outlines in organizing economic activity: motivation (getting people to expend effort, companies to allocate resources to an activity) and coordination (arranging activities so that they fit together, such as making sure a part needed for production arrives on time). There is an inherent trade-off between the two, also reflected Pisoni’s piece (control vs. empowerment is the most notable one). Alfred’s key point that this trade-off can be reduced (but not eliminate) through technology. For example, the evolution from a hub-and-spoke communication structure to a fully-mesh one enabled end-points to make informed decision without having to rely on a central decision-maker – better coordination without forcing a hit to motivation.

Now according to Pisoni’s all of that doesn’t matter, since responsiveness trumps efficiency. I (and others) however, are in a camp that believes that successful companies need to have both. More on that in the next post.

In it, they describe a cultural shift in American campuses – an attempt to shield young adults from words and ideas that make some uncomfortable, which they’ve labeled “protective vindictiveness”. It manifests itself in the form of growing accusations of “microaggressions” and requirements to issue “trigger warnings” (more on those in the article). Given that the aim of the movement is centered around emotional well-being, they use Cognitive Behavioral Therapy as a framework, to argue that it may be doing more harm than good on that front. Encouraging students to develop extra-thin skin, just before they go out into the “real world”, where they’ll encounter a plethora and words and ideas that they cannot control. It is worth reading their piece in full as I won’t be able to do it justice in summarizing it. In this short paragraph, I’ve probably already made some word choices that cased someone, somewhere to take offense…

But why am I covering a piece about campus culture in a blog about business organizational effectiveness? I’m glad you asked:

Today’s college culture problems are tomorrow’s business culture problems, as current students leave college and join the workforce, with this cultural indoctrination in mind.

Looking at the direction that typical “office sensitivity training programs” are headed, and the way that some related incidents are handled, some may argue that this culture has already started trickling into the work place.

Tech companies will be affected first as their demographic tends to skew young.

No matter on which side of the academic debate on “whether it’s the colleges’ job to prepare students for post-college life” you fall, this piece suggests that the skills/culture gap is widening. If colleges are not stepping up to address it (and some may argue, are making it worse), workplaces will have to.

With that last point in mind, Haidt and Lukianof suggest steps that can be taken to remediate the situation. Perhaps the most relevant one to the business world is teaching students (employees) how to practice Cognitive Behavioral Therapy, avoiding unhealthy emotional biases and applying more objective, critical thinking not only to the business problems they are tasked with solving, but more broadly to the way they chose to experience life.

Patty McCord, creator of the famous Netflix culture deck offers this relevant piece of advice: “97% of your employees will do the right thing. Most companies spend endless amount s of time and money writing and enforcing HR policies to deal with problems the other 3% might cause”.

Where C is the organizations’ capacity (max throughput), N is the number of people, α and β are the contention and coherence coefficients respectively.

Contention – measures the impact of waiting/queuing for resources on capacity, more commonly known as a the “bottleneck factor”. The contention coefficient reflects your ability to effectively delegate work and not become a bottleneck. Smaller coefficient reflects better delegating ability.

Coherence – measures the cost of getting agreement of what is the right thing to do. The coherence coefficient reflects the decision making autonomy within the organization. The more people need to be involved in making a decision, the higher the coefficient will be, and the capacity return from adding more people will decrease and may even become negative.

When trying not to become a bottleneck, we have to fight against our natural tendency to try and be helpful to anyone who asks us to help or contribute to a project. Little’s Law shows how by doing so we’re not being helpful at all:

average_wait_time = work_in_progress / throughput

Since our throughput is fixed (there are only that many hours in a day), the only thing we control is our “work in progress”, the number of concurrent projects we take on. The more projects we take on, the longer our average wait time gets and we become more and more of a bottleneck on these projects…

This gets compounded by the fact the request don’t come into our queue at a uniform rate. We know from Kingman’s Formula:

That as our utilization (ρ) increases, wait time increases exponentially. Working too close to 100% utilization will grind things to a halt. Adrian suggests choosing a WIP limit that will result in spending about 60% of your time on operational activities – ones that will slow down the rest of the org if you don’t process them promptly. The rest of those operational activities should either be delegated or discarded. The remaining 40% should be used for more strategic activities that will not have a negative cascading impact on the organization if they are put on hold during short-term periods of high operational load.

As a learning aid, metaphors are extremely useful. They help us understand something that’s new and unfamiliar by using something that’s familiar and better understood as a model.

But metaphors can also backfire. When they over-simply the system they intend to describe, they can lead to the wrong conclusion as to what would be an effective intervention in improving the system’s behavior.

This is exactly the point the Russell Ackoff and Jamshid Gharajedaghi made in their essay:

The way they affect the behavior / properties of the whole depends on the behavior of other parts in the system

They way groups of essential parts (subsystems) affect the behavior / properties of the whole depends on the behavior of other subsystems

They then define four types of system based on whether the whole, and its parts can display choice and the purposeful behavior which derives from it:

Deterministic systems: neither the parts nor the whole can display choice. Example: a Clock – both parts and whole are completely mechanistic)

Ecological systems: the parts can display choice but the whole cannot. Example: Nature – some parts of it (the animate parts – like people) can display choice. We can affect our environment, but the way the environment reacts to our actions is determined (though not always fully understood).

Animate systems: the parts cannot display choice, but the whole can. Example: a Person – we can make choices, but our organs cannot – their behavior is determined in a similar way to the behavior of an engine in a car. They do not make choices.

Social systems: both the parts and the whole can display choice. Example: Organization – but the parts (people) and the whole (organization) make choices.

Metaphors backfire and lead to wrong conclusions when they use a model of one type of system to describe a different type of system.

A recent example that I covered in this blog is Holacracy. Holacracy often uses the “operating system” metaphor to describe the way it interacts/affects the organizations in which it is implemented. When this metaphor is taken too far, it models the organization (social system) as a computer (deterministic system). And this is when things start to fall apart / diverge from reality.

I’ve been on vacation a few weeks back, driving more than 1,000 miles in between some of the most pristine day hikes in Virginia and North Carolina. Changing your routine almost always leads to a fresh perspective on issues you’ve been spending time thinking about, and this case was no different. I was thinking about Google.

Google has been desperately trying to diversify its lines of business further and further away from its search engine cash cow. Some of its more recent +$500M acquisitions were geared towards these new markets: Nest ($3.2B, home automation), Dropcam ($550M, home automation), Skybox Imaging ($500M, satellites), and Waze ($960M, GPS navigation). As well as its Moonshots portfolio: Google Glass, Project Loon and the Self-Driving Car project.

What all of those cutting-edge technology investments have in common, is that Google continues to apply them in the domain it knows best: directly to consumers. At least for Glass, that approach did not pan out well. Home automation does not seem to be panning out the way optimist may have expected. And when’s the last time we’ve heard about a new killer feature from Waze/Google Maps?

Consider a few (imaginary) press releases:

Google announces a shift of its Self-Driving Car project to be focused on trucks rather than consumer cars, as well as a partnership with Wal-Mart to transition its entire truck fleet to be autonomous by 2025 (

Google announces a partnership with Kaiser Permanente to equip surgeons in all of its hospitals with a Google Glass version customized to assist in surgeries (this is already sort-of happening)

Google announces a new fork of the Android OS called Dandroid designed to become the operating system for all commercial drones

Google announces a new product in its Maps portfolio called Waze Commercial aimed at becoming the platform for truck navigational assistance and freight tracking.

There are some interesting advantages in going with a businesses-first approach to adopting cutting edge technologies. An autocratic/centralized decision-making process, and a profit-driven motive can be leveraged to reach scale and drive adoption much quicker than in some direct-to-consumer scenarios.

There’s already regulatory progress in the UK to enable the testing of self-driving trucks. Meanwhile, companies like Airware (drones) and TruckerPath (trucks) are starting to capture incumbent positions with products that seem like not-so-radical extension of existing Google Products.

Granted, successfully building products for the enterprise requires a different type of corporate DNA than a consumer products company. But given that these growth areas are completely consistent with Google’s “to organize the world’s information…” mission, and Google’s sheer organizational size which should probably be able to support this kind of organizational diversity, if constructed thoughtfully, perhaps it’s time for a Google Commercial division?